def test_io_set():
"""Test importing EEGLAB .set files"""
from scipy import io
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
# main tests, and test missing event_id
_test_raw_reader(read_raw_eeglab,
input_fname=raw_fname,
montage=montage)
_test_raw_reader(read_raw_eeglab,
input_fname=raw_fname_onefile,
montage=montage)
for want in ('Events like', 'consist entirely', 'could not be mapped',
'string preload is not supported'):
assert_true(any(want in str(ww.message) for ww in w))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
# test finding events in continuous data
event_id = {'rt': 1, 'square': 2}
raw0 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id,
preload=True)
raw1 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id,
preload=False)
raw2 = read_raw_eeglab(input_fname=raw_fname_onefile,
montage=montage,
event_id=event_id)
raw3 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id)
raw4 = read_raw_eeglab(input_fname=raw_fname, montage=montage)
Epochs(raw0, find_events(raw0), event_id)
epochs = Epochs(raw1, find_events(raw1), event_id)
assert_equal(len(find_events(raw4)), 0) # no events without event_id
assert_equal(epochs["square"].average().nave, 80) # 80 with
assert_array_equal(raw0[:][0], raw1[:][0], raw2[:][0], raw3[:][0])
assert_array_equal(raw0[:][-1], raw1[:][-1], raw2[:][-1], raw3[:][-1])
assert_equal(len(w), 4)
# 1 for preload=False / str with fname_onefile, 3 for dropped events
raw0.filter(1,
None,
l_trans_bandwidth='auto',
filter_length='auto',
phase='zero') # test that preloading works
# test that using uint16_codec does not break stuff
raw0 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id,
preload=False,
uint16_codec='ascii')
# test old EEGLAB version event import
eeg = io.loadmat(raw_fname, struct_as_record=False, squeeze_me=True)['EEG']
for event in eeg.event: # old version allows integer events
event.type = 1
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
eeg.event = eeg.event[0] # single event
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
epochs = read_epochs_eeglab(epochs_fname)
epochs2 = read_epochs_eeglab(epochs_fname_onefile)
# one warning for each read_epochs_eeglab because both files have epochs
# associated with multiple events
assert_equal(len(w), 2)
assert_array_equal(epochs.get_data(), epochs2.get_data())
# test different combinations of events and event_ids
temp_dir = _TempDir()
out_fname = op.join(temp_dir, 'test-eve.fif')
write_events(out_fname, epochs.events)
event_id = {'S255/S8': 1, 'S8': 2, 'S255/S9': 3}
epochs = read_epochs_eeglab(epochs_fname, epochs.events, event_id)
assert_equal(len(epochs.events), 4)
assert_true(epochs.preload)
assert_true(epochs._bad_dropped)
epochs = read_epochs_eeglab(epochs_fname, out_fname, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname, None, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname, epochs.events,
None)
# test reading file with one event
eeg = io.loadmat(raw_fname, struct_as_record=False, squeeze_me=True)['EEG']
one_event_fname = op.join(temp_dir, 'test_one_event.set')
io.savemat(
one_event_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': eeg.nbchan,
'data': 'test_one_event.fdt',
'epoch': eeg.epoch,
'event': eeg.event[0],
'chanlocs': eeg.chanlocs,
'pnts': eeg.pnts
}
})
shutil.copyfile(op.join(base_dir, 'test_raw.fdt'),
op.join(temp_dir, 'test_one_event.fdt'))
event_id = {eeg.event[0].type: 1}
read_raw_eeglab(input_fname=one_event_fname,
montage=montage,
event_id=event_id,
preload=True)
# test reading file with one channel
one_chan_fname = op.join(temp_dir, 'test_one_channel.set')
io.savemat(
one_chan_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': 1,
'data': np.random.random((1, 3)),
'epoch': eeg.epoch,
'event': eeg.epoch,
'chanlocs': {
'labels': 'E1',
'Y': -6.6069,
'X': 6.3023,
'Z': -2.9423
},
'times': eeg.times[:3],
'pnts': 3
}
})
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
read_raw_eeglab(input_fname=one_chan_fname, preload=True)
# no warning for 'no events found'
assert_equal(len(w), 0)
# test reading file with 3 channels - one without position information
# first, create chanlocs structured array
ch_names = ['F3', 'unknown', 'FPz']
x, y, z = [1., 2., np.nan], [4., 5., np.nan], [7., 8., np.nan]
dt = [('labels', 'S10'), ('X', 'f8'), ('Y', 'f8'), ('Z', 'f8')]
chanlocs = np.zeros((3, ), dtype=dt)
for ind, vals in enumerate(zip(ch_names, x, y, z)):
for fld in range(4):
chanlocs[ind][dt[fld][0]] = vals[fld]
# save set file
one_chanpos_fname = op.join(temp_dir, 'test_chanpos.set')
io.savemat(
one_chanpos_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': 3,
'data': np.random.random((3, 3)),
'epoch': eeg.epoch,
'event': eeg.epoch,
'chanlocs': chanlocs,
'times': eeg.times[:3],
'pnts': 3
}
})
# load it
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
raw = read_raw_eeglab(input_fname=one_chanpos_fname, preload=True)
# one warning because some channels are not found in Montage
assert_equal(len(w), 1)
# position should be present for first two channels
for i in range(2):
assert_array_equal(
raw.info['chs'][i]['loc'][:3],
np.array([-chanlocs[i]['Y'], chanlocs[i]['X'], chanlocs[i]['Z']]))
# position of the last channel should be zero
assert_array_equal(raw.info['chs'][-1]['loc'][:3], np.array([0., 0., 0.]))
# test reading channel names from set and positions from montage
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
raw = read_raw_eeglab(input_fname=one_chanpos_fname,
preload=True,
montage=montage)
# one warning because some channels are not found in Montage
assert_equal(len(w), 1)
# when montage was passed - channel positions should be taken from there
correct_pos = [[-0.56705965, 0.67706631, 0.46906776], [0., 0., 0.],
[0., 0.99977915, -0.02101571]]
for ch_ind in range(3):
assert_array_almost_equal(raw.info['chs'][ch_ind]['loc'][:3],
np.array(correct_pos[ch_ind]))
# test reading channel names but not positions when there is no X (only Z)
# field in the EEG.chanlocs structure
nopos_chanlocs = chanlocs[['labels', 'Z']]
nopos_fname = op.join(temp_dir, 'test_no_chanpos.set')
io.savemat(
nopos_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': 3,
'data': np.random.random((3, 2)),
'epoch': eeg.epoch,
'event': eeg.epoch,
'chanlocs': nopos_chanlocs,
'times': eeg.times[:2],
'pnts': 2
}
})
# load the file
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
raw = read_raw_eeglab(input_fname=nopos_fname, preload=True)
# test that channel names have been loaded but not channel positions
for i in range(3):
assert_equal(raw.info['chs'][i]['ch_name'], ch_names[i])
assert_array_equal(raw.info['chs'][i]['loc'][:3],
np.array([0., 0., 0.]))
# test if .dat file raises an error
eeg = io.loadmat(epochs_fname, struct_as_record=False,
squeeze_me=True)['EEG']
eeg.data = 'epochs_fname.dat'
bad_epochs_fname = op.join(temp_dir, 'test_epochs.set')
io.savemat(
bad_epochs_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': eeg.nbchan,
'data': eeg.data,
'epoch': eeg.epoch,
'event': eeg.event,
'chanlocs': eeg.chanlocs
}
})
shutil.copyfile(op.join(base_dir, 'test_epochs.fdt'),
op.join(temp_dir, 'test_epochs.dat'))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
assert_raises(NotImplementedError, read_epochs_eeglab,
bad_epochs_fname)
assert_equal(len(w), 1)
def test_io_set():
"""Test importing EEGLAB .set files"""
from scipy import io
with warnings.catch_warnings(record=True) as w1:
warnings.simplefilter('always')
# main tests, and test missing event_id
_test_raw_reader(read_raw_eeglab, input_fname=raw_fname,
montage=montage)
_test_raw_reader(read_raw_eeglab, input_fname=raw_fname_onefile,
montage=montage)
assert_equal(len(w1), 20)
# f3 or preload_false and a lot for dropping events
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
# test finding events in continuous data
event_id = {'rt': 1, 'square': 2}
raw0 = read_raw_eeglab(input_fname=raw_fname, montage=montage,
event_id=event_id, preload=True)
raw1 = read_raw_eeglab(input_fname=raw_fname, montage=montage,
event_id=event_id, preload=False)
raw2 = read_raw_eeglab(input_fname=raw_fname_onefile, montage=montage,
event_id=event_id)
raw3 = read_raw_eeglab(input_fname=raw_fname, montage=montage,
event_id=event_id)
raw4 = read_raw_eeglab(input_fname=raw_fname, montage=montage)
Epochs(raw0, find_events(raw0), event_id)
epochs = Epochs(raw1, find_events(raw1), event_id)
assert_equal(len(find_events(raw4)), 0) # no events without event_id
assert_equal(epochs["square"].average().nave, 80) # 80 with
assert_array_equal(raw0[:][0], raw1[:][0], raw2[:][0], raw3[:][0])
assert_array_equal(raw0[:][-1], raw1[:][-1], raw2[:][-1], raw3[:][-1])
assert_equal(len(w), 4)
# 1 for preload=False / str with fname_onefile, 3 for dropped events
raw0.filter(1, None, l_trans_bandwidth='auto', filter_length='auto',
phase='zero') # test that preloading works
# test that using uin16_codec does not break stuff
raw0 = read_raw_eeglab(input_fname=raw_fname, montage=montage,
event_id=event_id, preload=False,
uint16_codec='ascii')
# test old EEGLAB version event import
eeg = io.loadmat(raw_fname, struct_as_record=False,
squeeze_me=True)['EEG']
for event in eeg.event: # old version allows integer events
event.type = 1
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
eeg.event = eeg.event[0] # single event
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
epochs = read_epochs_eeglab(epochs_fname)
epochs2 = read_epochs_eeglab(epochs_fname_onefile)
# one warning for each read_epochs_eeglab because both files have epochs
# associated with multiple events
assert_equal(len(w), 2)
assert_array_equal(epochs.get_data(), epochs2.get_data())
# test different combinations of events and event_ids
temp_dir = _TempDir()
out_fname = op.join(temp_dir, 'test-eve.fif')
write_events(out_fname, epochs.events)
event_id = {'S255/S8': 1, 'S8': 2, 'S255/S9': 3}
epochs = read_epochs_eeglab(epochs_fname, epochs.events, event_id)
assert_equal(len(epochs.events), 4)
epochs = read_epochs_eeglab(epochs_fname, out_fname, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname,
None, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname,
epochs.events, None)
# test reading file with one event
eeg = io.loadmat(raw_fname, struct_as_record=False,
squeeze_me=True)['EEG']
one_event_fname = op.join(temp_dir, 'test_one_event.set')
io.savemat(one_event_fname, {'EEG':
{'trials': eeg.trials, 'srate': eeg.srate,
'nbchan': eeg.nbchan, 'data': 'test_one_event.fdt',
'epoch': eeg.epoch, 'event': eeg.event[0],
'chanlocs': eeg.chanlocs, 'pnts': eeg.pnts}})
shutil.copyfile(op.join(base_dir, 'test_raw.fdt'),
op.join(temp_dir, 'test_one_event.fdt'))
event_id = {eeg.event[0].type: 1}
read_raw_eeglab(input_fname=one_event_fname, montage=montage,
event_id=event_id, preload=True)
# test reading file with one channel
one_chan_fname = op.join(temp_dir, 'test_one_channel.set')
io.savemat(one_chan_fname, {'EEG':
{'trials': eeg.trials, 'srate': eeg.srate,
'nbchan': 1, 'data': np.random.random((1, 3)),
'epoch': eeg.epoch, 'event': eeg.epoch,
'chanlocs': {'labels': 'E1', 'Y': -6.6069,
'X': 6.3023, 'Z': -2.9423},
'times': eeg.times[:3], 'pnts': 3}})
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
read_raw_eeglab(input_fname=one_chan_fname, preload=True)
# no warning for 'no events found'
assert_equal(len(w), 0)
# test if .dat file raises an error
eeg = io.loadmat(epochs_fname, struct_as_record=False,
squeeze_me=True)['EEG']
eeg.data = 'epochs_fname.dat'
bad_epochs_fname = op.join(temp_dir, 'test_epochs.set')
io.savemat(bad_epochs_fname, {'EEG':
{'trials': eeg.trials, 'srate': eeg.srate,
'nbchan': eeg.nbchan, 'data': eeg.data,
'epoch': eeg.epoch, 'event': eeg.event,
'chanlocs': eeg.chanlocs}})
shutil.copyfile(op.join(base_dir, 'test_epochs.fdt'),
op.join(temp_dir, 'test_epochs.dat'))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
assert_raises(NotImplementedError, read_epochs_eeglab,
bad_epochs_fname)
assert_equal(len(w), 1)
def test_io_set():
"""Test importing EEGLAB .set files"""
from scipy import io
with warnings.catch_warnings(record=True) as w1:
warnings.simplefilter("always")
# main tests, and test missing event_id
_test_raw_reader(read_raw_eeglab, input_fname=raw_fname, montage=montage)
_test_raw_reader(read_raw_eeglab, input_fname=raw_fname_onefile, montage=montage)
assert_equal(len(w1), 20)
# f3 or preload_false and a lot for dropping events
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
# test finding events in continuous data
event_id = {"rt": 1, "square": 2}
raw0 = read_raw_eeglab(input_fname=raw_fname, montage=montage, event_id=event_id, preload=True)
raw1 = read_raw_eeglab(input_fname=raw_fname, montage=montage, event_id=event_id, preload=False)
raw2 = read_raw_eeglab(input_fname=raw_fname_onefile, montage=montage, event_id=event_id)
raw3 = read_raw_eeglab(input_fname=raw_fname, montage=montage, event_id=event_id)
raw4 = read_raw_eeglab(input_fname=raw_fname, montage=montage)
Epochs(raw0, find_events(raw0), event_id)
epochs = Epochs(raw1, find_events(raw1), event_id)
assert_equal(len(find_events(raw4)), 0) # no events without event_id
assert_equal(epochs["square"].average().nave, 80) # 80 with
assert_array_equal(raw0[:][0], raw1[:][0], raw2[:][0], raw3[:][0])
assert_array_equal(raw0[:][-1], raw1[:][-1], raw2[:][-1], raw3[:][-1])
assert_equal(len(w), 4)
# 1 for preload=False / str with fname_onefile, 3 for dropped events
raw0.filter(1, None, l_trans_bandwidth="auto", filter_length="auto", phase="zero") # test that preloading works
# test that using uint16_codec does not break stuff
raw0 = read_raw_eeglab(
input_fname=raw_fname, montage=montage, event_id=event_id, preload=False, uint16_codec="ascii"
)
# test old EEGLAB version event import
eeg = io.loadmat(raw_fname, struct_as_record=False, squeeze_me=True)["EEG"]
for event in eeg.event: # old version allows integer events
event.type = 1
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
eeg.event = eeg.event[0] # single event
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
epochs = read_epochs_eeglab(epochs_fname)
epochs2 = read_epochs_eeglab(epochs_fname_onefile)
# one warning for each read_epochs_eeglab because both files have epochs
# associated with multiple events
assert_equal(len(w), 2)
assert_array_equal(epochs.get_data(), epochs2.get_data())
# test different combinations of events and event_ids
temp_dir = _TempDir()
out_fname = op.join(temp_dir, "test-eve.fif")
write_events(out_fname, epochs.events)
event_id = {"S255/S8": 1, "S8": 2, "S255/S9": 3}
epochs = read_epochs_eeglab(epochs_fname, epochs.events, event_id)
assert_equal(len(epochs.events), 4)
assert_true(epochs.preload)
assert_true(epochs._bad_dropped)
epochs = read_epochs_eeglab(epochs_fname, out_fname, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname, None, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname, epochs.events, None)
# test reading file with one event
eeg = io.loadmat(raw_fname, struct_as_record=False, squeeze_me=True)["EEG"]
one_event_fname = op.join(temp_dir, "test_one_event.set")
io.savemat(
one_event_fname,
{
"EEG": {
"trials": eeg.trials,
"srate": eeg.srate,
"nbchan": eeg.nbchan,
"data": "test_one_event.fdt",
"epoch": eeg.epoch,
"event": eeg.event[0],
"chanlocs": eeg.chanlocs,
"pnts": eeg.pnts,
}
},
)
shutil.copyfile(op.join(base_dir, "test_raw.fdt"), op.join(temp_dir, "test_one_event.fdt"))
event_id = {eeg.event[0].type: 1}
read_raw_eeglab(input_fname=one_event_fname, montage=montage, event_id=event_id, preload=True)
# test reading file with one channel
one_chan_fname = op.join(temp_dir, "test_one_channel.set")
io.savemat(
one_chan_fname,
{
"EEG": {
"trials": eeg.trials,
"srate": eeg.srate,
"nbchan": 1,
"data": np.random.random((1, 3)),
"epoch": eeg.epoch,
"event": eeg.epoch,
"chanlocs": {"labels": "E1", "Y": -6.6069, "X": 6.3023, "Z": -2.9423},
"times": eeg.times[:3],
"pnts": 3,
}
},
)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
read_raw_eeglab(input_fname=one_chan_fname, preload=True)
# no warning for 'no events found'
assert_equal(len(w), 0)
# test if .dat file raises an error
eeg = io.loadmat(epochs_fname, struct_as_record=False, squeeze_me=True)["EEG"]
eeg.data = "epochs_fname.dat"
bad_epochs_fname = op.join(temp_dir, "test_epochs.set")
io.savemat(
bad_epochs_fname,
{
"EEG": {
"trials": eeg.trials,
"srate": eeg.srate,
"nbchan": eeg.nbchan,
"data": eeg.data,
"epoch": eeg.epoch,
"event": eeg.event,
"chanlocs": eeg.chanlocs,
}
},
)
shutil.copyfile(op.join(base_dir, "test_epochs.fdt"), op.join(temp_dir, "test_epochs.dat"))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
assert_raises(NotImplementedError, read_epochs_eeglab, bad_epochs_fname)
assert_equal(len(w), 1)
def test_io_set():
"""Test importing EEGLAB .set files"""
from scipy import io
with warnings.catch_warnings(record=True) as w1:
warnings.simplefilter('always')
# main tests, and test missing event_id
_test_raw_reader(read_raw_eeglab,
input_fname=raw_fname,
montage=montage)
_test_raw_reader(read_raw_eeglab,
input_fname=raw_fname_onefile,
montage=montage)
assert_equal(len(w1), 20)
# f3 or preload_false and a lot for dropping events
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
# test finding events in continuous data
event_id = {'rt': 1, 'square': 2}
raw0 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id,
preload=True)
raw1 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id,
preload=False)
raw2 = read_raw_eeglab(input_fname=raw_fname_onefile,
montage=montage,
event_id=event_id)
raw3 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id)
raw4 = read_raw_eeglab(input_fname=raw_fname, montage=montage)
Epochs(raw0, find_events(raw0), event_id, add_eeg_ref=False)
epochs = Epochs(raw1, find_events(raw1), event_id, add_eeg_ref=False)
assert_equal(len(find_events(raw4)), 0) # no events without event_id
assert_equal(epochs["square"].average().nave, 80) # 80 with
assert_array_equal(raw0[:][0], raw1[:][0], raw2[:][0], raw3[:][0])
assert_array_equal(raw0[:][-1], raw1[:][-1], raw2[:][-1], raw3[:][-1])
assert_equal(len(w), 4)
# 1 for preload=False / str with fname_onefile, 3 for dropped events
raw0.filter(1,
None,
l_trans_bandwidth='auto',
filter_length='auto',
phase='zero') # test that preloading works
# test that using uin16_codec does not break stuff
raw0 = read_raw_eeglab(input_fname=raw_fname,
montage=montage,
event_id=event_id,
preload=False,
uint16_codec='ascii')
# test old EEGLAB version event import
eeg = io.loadmat(raw_fname, struct_as_record=False, squeeze_me=True)['EEG']
for event in eeg.event: # old version allows integer events
event.type = 1
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
eeg.event = eeg.event[0] # single event
assert_equal(_read_eeglab_events(eeg)[-1, -1], 1)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
epochs = read_epochs_eeglab(epochs_fname)
epochs2 = read_epochs_eeglab(epochs_fname_onefile)
# one warning for each read_epochs_eeglab because both files have epochs
# associated with multiple events
assert_equal(len(w), 2)
assert_array_equal(epochs.get_data(), epochs2.get_data())
# test different combinations of events and event_ids
temp_dir = _TempDir()
out_fname = op.join(temp_dir, 'test-eve.fif')
write_events(out_fname, epochs.events)
event_id = {'S255/S8': 1, 'S8': 2, 'S255/S9': 3}
epochs = read_epochs_eeglab(epochs_fname, epochs.events, event_id)
assert_equal(len(epochs.events), 4)
epochs = read_epochs_eeglab(epochs_fname, out_fname, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname, None, event_id)
assert_raises(ValueError, read_epochs_eeglab, epochs_fname, epochs.events,
None)
# test reading file with one event
eeg = io.loadmat(raw_fname, struct_as_record=False, squeeze_me=True)['EEG']
one_event_fname = op.join(temp_dir, 'test_one_event.set')
io.savemat(
one_event_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': eeg.nbchan,
'data': 'test_one_event.fdt',
'epoch': eeg.epoch,
'event': eeg.event[0],
'chanlocs': eeg.chanlocs,
'pnts': eeg.pnts
}
})
shutil.copyfile(op.join(base_dir, 'test_raw.fdt'),
op.join(temp_dir, 'test_one_event.fdt'))
event_id = {eeg.event[0].type: 1}
read_raw_eeglab(input_fname=one_event_fname,
montage=montage,
event_id=event_id,
preload=True)
# test reading file with one channel
one_chan_fname = op.join(temp_dir, 'test_one_channel.set')
io.savemat(
one_chan_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': 1,
'data': np.random.random((1, 3)),
'epoch': eeg.epoch,
'event': eeg.epoch,
'chanlocs': {
'labels': 'E1',
'Y': -6.6069,
'X': 6.3023,
'Z': -2.9423
},
'times': eeg.times[:3],
'pnts': 3
}
})
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
read_raw_eeglab(input_fname=one_chan_fname, preload=True)
# no warning for 'no events found'
assert_equal(len(w), 0)
# test if .dat file raises an error
eeg = io.loadmat(epochs_fname, struct_as_record=False,
squeeze_me=True)['EEG']
eeg.data = 'epochs_fname.dat'
bad_epochs_fname = op.join(temp_dir, 'test_epochs.set')
io.savemat(
bad_epochs_fname, {
'EEG': {
'trials': eeg.trials,
'srate': eeg.srate,
'nbchan': eeg.nbchan,
'data': eeg.data,
'epoch': eeg.epoch,
'event': eeg.event,
'chanlocs': eeg.chanlocs
}
})
shutil.copyfile(op.join(base_dir, 'test_epochs.fdt'),
op.join(temp_dir, 'test_epochs.dat'))
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
assert_raises(NotImplementedError, read_epochs_eeglab,
bad_epochs_fname)
assert_equal(len(w), 1)